It is not unusual in higher education to present enrollment
data disaggregated by race/ethnicity. These data demonstrate
who enrolls and whether enrollees reflect the nation’s
demography and goals for equitable access to higher
education. Unfortunately, such presentations are usually
confined to simple enrollment data with limited exploration
of students’ campus-based experiences and outcomes.
Indeed, where these enrollment data provide some numerical
evidence of a diverse campus, there is usually an assumption
that there is an institutional commitment to achieving
equitable access for those traditionally underrepresented.
Such is the power of data in shaping the perceptions
of progress regarding diversity in higher education.
Our work in the Campus Diversity Initiative (CDI) Evaluation
Project, however, has taught us that simply reviewing
data devoid of an evaluative context may both mask large
inequities and minimize important institutional gains
to which diversity efforts contribute. If data are not
collected and analyzed for the purpose of evaluating
programs in light of institutional goals, then the powerful
tool of data can easily become little more than campus
propaganda. A major goal of the CDI Evaluation Project
is for campuses to develop evaluation capacity to improve
their programs, practices, and policies relative to
institutional goals for diversity—what we refer
to as organizational learning.

Senior administrators’ first question is often,
“What do you need those data for?” Our response
is that they need the data if they are to reach their
institutional goals. We explain that the purposes of
data in the context of institutional learning are to
test assumptions, identify gaps in knowledge, initiate
and guide dialogue, and provide direction for improvement.
While the question initially may be prompted by fears
that data could be misused, when campus constituencies
understand these larger purposes, data becomes a powerful
tool.

The type of data to be collected also creates anxieties
about capacity and management. We have observed from
working with the 28 CDI grantee campuses that the most
useful data often already exists on campuses. Often
referred to as “routine data” (Bauman &
Bensimon 2002), this information is usually shelved
away in reports produced by institutional research offices,
strategic planning exercises, or past diversity reports.
These data are often in the form of campus surveys,
departmental reviews, and enrollment reports. When disaggregated
by race/ethnicity and other important dimensions, such
routine data can provide tremendous learning opportunities
for individual offices and the institution overall,
especially when placed in the context of evaluation
for the purpose of organizational learning.

For example, choosing to improve the campus climate
as it relates to diversity as one of its CDI efforts,
one campus analyzed existing student survey data to
determine the strategies it would use. The results showed
that a higher proportion of students who participated
in cultural awareness workshops reported greater levels
of satisfaction with the campus climate for minority
students. This data analysis led to the immediate conclusion
that an expansion of cultural awareness workshops was
a good strategy.

When survey responses
were disaggregated by race/ethnicity, a different
picture emerged. African American and Asian American
students who participated in cultural awareness
workshops reported lower levels of satisfaction
with the campus climate for minorities than those
who did not participate in those workshops.

However, when survey responses were disaggregated by
race/ethnicity, a different picture emerged. African
American and Asian American students who participated
in cultural awareness workshops reported lower levels
of satisfaction with the campus climate for minorities
than those who did not participate in those workshops.
In addition, Asian Americans as a group reported the
highest level of satisfaction with the campus climate
for minorities. While White students’ level of
satisfaction appeared to be the lowest among all groups,
closer examination of the data showed that this was
an effect of over 40 percent of White students having
responded “not relevant” to the satisfaction
question, whereas this response was less than 5 percent
for all other groups. These findings suggest that careful
consideration be given to how varied groups experience
these types of programs, and whether the program content
addresses their needs and concerns. Disaggregated institutional
data can suggest exciting prospects for overcoming the
marginality experienced by some groups on campus.

The emphasis on data collection and utilization has
provided important learning opportunities for some campuses
that look to higher education research to inform their
practice. For example, the general consensus in the
retention literature is that the first year is a critical
stage for campus retention efforts. Based on the literature,
if students survive the first year and enroll for their
second year, their chances of graduating greatly increase.
As part of the evaluation process, campuses submit year-to-year
persistence data disaggregated by race/ethnicity with
four and six-year graduation rates. As we analyzed the
data of one campus, we noticed an interesting, but disturbing
trend. The attrition for Latino/a and African American
students was not occurring solely at the points where
the literature suggests. Even though their first-year
persistence rates were similar to the overall campus
rate of 80%, a higher proportion of Latino/a and African
American students tended to leave after their 2nd and
3rd years respectively as compared to their Asian American
and White counterparts (Figure Below). However, for
American Indian students the point of attrition was
still the first year. Knowing this has allowed campus
officials and program directors to reconsider some of
their strategies and to explore further reasons for
this situation.

In addition, data can inform a campus of its mixture
of success and failure. While a campus may have been
successful in making sure that Latino/a and African
American students survive that critical first year,
by not developing a more comprehensive view of retention,
they may have missed a critical attrition point in later
years for Latino/a and African American students. Additionally,
by fully disaggregating the data by racial/ethnic groups
on campus, officials can determine the attrition points
for Asian American and White students for whom there
might have been less concern about their points of attrition,
given their relatively higher graduation rates. By having
this disaggregated data, a campus can further develop
programs and practices that are campus specific and
data informed.

There are other reasons that campuses may not use existing
data. One reason is that campuses do not have a position
designated as institutional researcher. However, most
campuses have talented and skilled researchers on their
faculty or staff whose expertise could be tapped to
analyze data for institutional learning. Fear of losing
control over the data or inciting conflict on campus
is another reason campuses fail to collect, analyze,
and disseminate institutional data. But, by failing
to do so, campuses run the risk of ignoring effective
diversity strategies and not learning from their failures
and successes.

Source

Bauman, G. L. & E. M. Bensimon. 2002. The Promotion
of organizational learning through the use of routine
data. Paper presented at the Annual Meeting of the Association
for the Study of Higher Education. November 22. Sacramento,
CA.